University of Groningen

Plasma Malondialdehyde and Risk of New-Onset Diabetes after Transplantation in RenalTransplant RecipientsYepes-Calderon, Manuela; Sotomayor, Camilo G.; Gomes-Neto, Antonio W.; Gans, Rijk O.B.; Berger, Stefan P.; Rimbach, Gerald; Esatbeyoglu, Tuba; Rodrigo, Ramon; Geleijnse,Johanna M.; Navis, Gerjan J.Published in:Journal of Clinical Medicine

DOI:10.3390/jcm8040453

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Citation for published version (APA):Yepes-Calderon, M., Sotomayor, C. G., Gomes-Neto, A. W., Gans, R. O. B., Berger, S. P., Rimbach, G., ...Bakker, S. J. L. (2019). Plasma Malondialdehyde and Risk of New-Onset Diabetes after Transplantation inRenal Transplant Recipients: A Prospective Cohort Study. Journal of Clinical Medicine, 8(4), [453].https://doi.org/10.3390/jcm8040453

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Journal of

Clinical Medicine

Article

Plasma Malondialdehyde and Risk of New-OnsetDiabetes after Transplantation in Renal TransplantRecipients: A Prospective Cohort Study

Manuela Yepes-Calderón 1, Camilo G. Sotomayor 1,* , António W. Gomes-Neto 1,Rijk O.B. Gans 2, Stefan P. Berger 1, Gerald Rimbach 3, Tuba Esatbeyoglu 4, Ramón Rodrigo 5 ,Johanna M. Geleijnse 6 , Gerjan J. Navis 1 and Stephan J.L. Bakker 1

1 Division of Nephrology, Department of Internal Medicine, University Medical Center Groningen,University of Groningen, 9713 GZ Groningen, The Netherlands; manueyepes@gmail.com (M.Y.-C.);a.w.gomes.neto@umcg.nl (A.W.G.-N.); s.p.berger@umcg.nl (S.P.B.); g.j.navis@umcg.nl (G.J.N.);s.j.l.bakker@umcg.nl (S.J.L.B.)

2 Department of Internal Medicine, University Medical Center Groningen, University of Groningen,9713 GZ Groningen, The Netherlands; r.o.b.gans@umcg.nl

3 Institute of Human Nutrition and Food Science, Christian-Albrechts-University of Kiel, HerrmannRodewaldstrasse 6, D-24118 Kiel, Germany; rimbach@foodsci.uni-kiel.de

4 Institute of Food Science and Human Nutrition, Department Food Development and Food Quality,Gottfried Wilhelm Leibniz University Hannover, Am Kleinen Felde 30, D-30167 Hannover, Germany;esatbeyoglu@lw.uni-hannover.de

5 Molecular and Clinical Pharmacology Program, Institute of Biomedical Sciences, Faculty of Medicine,University of Chile, Av. Independencia 1027, CP 8380453 Santiago, Chile; rrodrigo@med.uchile.cl

6 Division of Human Nutrition and Health, Wageningen University and Research, P.O. Box 47,6700 AA Wageningen, The Netherlands; Marianne.geleijnse@wur.nl

* Correspondence: c.g.sotomayor.campos@umcg.nl; Tel.: +31-061-921-08-81

Received: 17 February 2019; Accepted: 30 March 2019; Published: 4 April 2019�����������������

Abstract: New-onset diabetes after transplantation (NODAT) is a frequent complication in renaltransplant recipients (RTR). Although oxidative stress has been associated with diabetes mellitus,data regarding NODAT are limited. We aimed to prospectively investigate the long-term associationbetween the oxidative stress biomarker malondialdehyde (measured by high-performance liquidchromatography) and NODAT in an extensively phenotyped cohort of non-diabetic RTR with afunctioning graft ≥1 year. We included 516 RTR (51 ± 13 years-old, 57% male). Median plasmamalondialdehyde (MDA) was 2.55 (IQR, 1.92–3.66) µmol/L. During a median follow-up of 5.3(IQR, 4.6–6.0) years, 56 (11%) RTR developed NODAT. In Cox proportional-hazards regressionanalyses, MDA was inversely associated with NODAT, independent of immunosuppressive therapy,transplant-specific covariates, lifestyle, inflammation, and metabolism parameters (HR, 0.55; 95%CI, 0.36–0.83 per 1-SD increase; p < 0.01). Dietary antioxidants intake (e.g., vitamin E, α-lipoicacid, and linoleic acid) were effect-modifiers of the association between MDA and NODAT,with particularly strong inverse associations within the subgroup of RTR with relatively higherdietary antioxidants intake. In conclusion, plasma MDA concentration is inversely and independentlyassociated with long-term risk of NODAT in RTR. Our findings support a potential underrecognizedrole of oxidative stress in post-transplantation glucose homeostasis.

Keywords: malondialdehyde; oxidative stress; new-onset diabetes; renal transplantation

J. Clin. Med. 2019, 8, 453; doi:10.3390/jcm8040453 www.mdpi.com/journal/jcm

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1. Introduction

New-onset diabetes after transplantation (NODAT) is a major metabolic complication of solidorgan transplantation, with a reported incidence of up to 50% [1]. Consequences of NODAT aredetrimental for renal transplant recipients (RTR) as it is associated with reduced recipient survival,increased rate of cardiovascular events, and impaired graft survival in the long term [2,3]. In theera of high-dose steroid regimens, twelve-months cumulative incidence of NODAT was significantlyhigher, and the main risk factor identified for the occurrence of NODAT was immunosuppressanttherapy [3]. However, with new cyclosporine-based and tacrolimus-based regimens [1,4], it iswell-documented that the largest number of incident cases of NODAT occurred, indeed, after the firstyear of transplantation [4,5], and other agents potentially involved in the long-term pathogenesis ofthe disease remain to be elucidated. In order to improve the outcomes of RTR, it is of great interest toknow which factors contribute to this long-term NODAT development and maintenance [2].

Oxidative stress (OS) is a factor that in different studies has been linked with both physiologicalresponse to insulin and pathophysiological mechanisms of, e.g., diabetes mellitus; it is also knownto be enhanced in RTR when compared to general population [6]. Higher levels of OS biomarkers,e.g., MDA [7], have been found in patients with established diabetes mellitus compared to healthycontrols [8], and in patients with diabetes-associated complications compared to patients withnoncomplicated diabetes [9]. However, a developing body of evidence has linked oxidativespecies with insulin signaling [10–13], and it has been postulated that diabetes mellitus is—to aconsiderable extent—caused by a failure of the organism to create enough oxidative redox potential [14].There is, nevertheless, only limited data relating OS with insulin resistance in prediabetes states [15].Furthermore, to the extent of our knowledge, no longitudinal studies have aimed to study theassociation between OS biomarkers and long-term incidence of diabetes, which makes it difficult toforesee whether OS biomarkers may prospectively be associated with positive or negative outcomesregarding glucose metabolism outcomes.

In post-transplantation setting, less evidence is available regarding the role of OS on glucosehomeostasis. Indeed, the long-term prospective association of systemic OS and the developmentof NODAT has not been explored. The primary objective of the present study was set to test thehypothesis that post-transplantation OS is associated with the development of NODAT. Furthermore,by considering evidence reporting an effect of dietary antioxidant intake on the development of type2 diabetes and NODAT [16,17], we aimed to assess whether the potential association of MDA withNODAT may be modified by regular dietary antioxidant fatty acids intake. Finally, we investigatedwhether OS is associated with the secondary end-points of long-term all-cause mortality, cardiovascularmortality, and graft failure.

2. Materials and Methods

2.1. Study Design and Patient Population

In this prospective cohort study, all adult RTR with a functioning graft for at least one yearwho visited the outpatient clinic at the University Medical Center of Groningen (The Netherlands)between November 2008 and May 2011 were considered eligible to participate. Baseline data wasobtained at least one year after transplantation with a median of five years. We excluded RTR withdiabetes mellitus at baseline or before transplant (defined as fasting plasma glucose ≥126 mg/dL(7.0 mmol/L) and/or use of glucose lowering drugs) (n = 173); also patients who underwent combinedpancreas-kidney transplantation (n = 5) or whose plasma MDA concentration measurement at baselinewas missing (n = 12), resulting in 516 RTR eligible for statistical analyses. The patients were followed-upuntil 1 April 2014. Collection of these data was ensured by the continuous surveillance system of theoutpatient clinic of our university hospital and close collaboration with affiliated hospitals. Follow-upwas performed according to the guidelines of the American Society of Transplantation [18].

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The primary end-point of the current study was the long-term development of NODAT. Secondaryend points were all cause-mortality, cardiovascular mortality, and graft failure. No participantswere lost due to follow-up. The current study was approved by the institutional review board(METc 2008/186) and adhered to the Declarations of Helsinki and Istanbul.

2.2. Data Collection

Baseline data was collected during a visit to the outpatient clinic, following a detailed protocoldescribed elsewhere [19]. Anthropometric measurements were taken while participants wore indoorclothing without shoes. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) weremeasured using a semiautomatic device (Dinamap1846; Critikon, Tampa, FL, USA) every minute for15 min, following a strict protocol as described before [20].

Three questionnaires were administered to patients: first, the Short QUestionnaire to ASsessHealth-enhancing physical activity (SQUASH) score for information about the daily physicalactivity [21]. Second, a questionnaire regarding smoking behavior to classify patients as current,previous or never smokers. Third, a semiquantitative self-administered food frequency questionnaire(FFQ) of 177 items to collect information on dietary intake during the past month. The FFQ wasdeveloped at Wageningen university, previously validated for our population, and it has been updatedseveral times [22]. Number of servings was recorded in natural units (e.g., slice of bread) or householdmeasures (e.g., a teaspoon). Subsequently, all dietary data were converted into total energy andnutrient intake per day, using the Dutch Food Composition Table 2006 [23]. Specific nutrient intakeswere adjusted for total energy intake according to the residual method [24].

Of note, except for discouraging excess sodium intake and encouraging weight loss in overweightindividuals, no specific dietary counseling was included, nor was dietary recommendation regardingantioxidant fatty acids intake or supplementation advised to the study subjects. Other relevantrecipient and transplant information was extracted from the Groningen Renal Transplant Database,as described in detail before [25].

2.3. Measurements and Definitions

Fasting blood samples and complete 24-hour urine collection were taken at baseline. Serumcreatinine was determined by using the Jaffe reaction (MEGA AU510; Merck Diagnostica, Darmstadt,Germany); plasma glucose by the glucose oxidase method (YSI 2300 Stat Plus; Yellow Springs Instruments,Yellow Springs, OH, USA); total cholesterol by the cholesterol oxidase-phenol aminophenazone method(MEGA AU510); HDL cholesterol by the cholesterol oxidase-phenol aminophenazone method on aTechnicon RA-1000 (Bayer Diagnostics, Mijdrecht, the Netherlands); and plasma triglycerides by theglycerol-3-phosphate oxidase-oxidase method (YSI 2300 Stat Plus). LDL cholesterol was calculated byusing the Friedewald equation; estimated glomerular filtration rate (eGFR) by the serum creatinine basedChronic Kidney Disease EPIdemiology collaboration equation (CKD-EPI) [26]; and the cumulative dose ofprednisolone as the sum of the maintenance dose of prednisolone from transplantation until baseline. PlasmaMDA concentration was chosen as the biomarker of OS because it has been used before in studies regardingpathologies of the glucose metabolism [8,9]; it was measured by high-performance liquid chromatographywith a photodiode array detector as described by Faizan et al. to improve the sensitivity offered byspectrophotometrically methods [27].

NODAT was defined according to the International Expert Panel recommendations based on the2003 American Diabetes Association criteria [28] and the HbA1c criterion proposed by the InternationalExpert Panel of the international consensus meeting on post transplantation diabetes mellitus [29].The diagnosis was made with the fulfillment of one or more of the following: symptoms of diabetes(classic symptoms, including polyuria, polydipsia, and unexplained weight loss) plus random plasmaglucose concentration≥200 mg/dL (11.1 mmol/L); fasting plasma glucose≥126 mg/dL (7.0 mmol/L);plasma HbA1c ≥ 6.5%; or use of glucose-lowering medication. If fasting plasma glucose was elevated,a confirmatory laboratory test was performed, after which the diagnosis of NODAT was made.

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Cardiovascular death was defined as the principal cause of death being cardiovascular in nature(International Classification of Diseases (ICD)-9 codes 410–447). The cause of death was obtained bylinking the number of the death certificate to the primary cause of death as coded by a physician fromthe Central Bureau of Statistics according to the ICD-9 [30]. Graft failure was defined as restart ofdialysis or retransplantation.

2.4. Statistical Analyses

Data analyses, computations, and graphs were performed with SPSS 22.0 software (IBMCorporation, Chicago, IL, USA), R version 3.2.3 software (The R-Foundation for Statistical Computing,Vienna, Austria), and GraphPad Prism version 7 software (GraphPad Software, San Diego, CA, USA).

For descriptive statistics data are presented as mean± standard deviation (SD) for normally distributeddata, and as median (interquartile range (IQR)) for variables with a non-normal distribution. Categoricaldata are expressed as number (percentage). Crude and age, sex, and eGFR-adjusted linear regressionanalyses were performed to examine the association of baseline characteristics with circulating MDA.Residuals were checked for normality and natural log-transformed when appropriate. In order to study inan integrated manner which baseline variables were independently associated with and were determinantsof circulating MDA, we performed stepwise backwards multivariable linear regression analyses. Forinclusion and exclusion in these analyses, p-values were set at 0.2 and 0.05, respectively.

NODAT development was visualized by Kaplan–Meier curves according to tertiles of plasmaMDA concentration, with statistical significance among curves tested by log-rank (Mantel–Cox) test.The prospective association of plasma MDA concentration with the different outcomes was assessedthrough Cox regression analyses. We first performed crude analyses followed by additive adjustmentsfor demographic and anthropometric factors (age, sex, and BMI) in model 1; metabolism-relatedvariables (glucose, HbA1c, and HDL cholesterol) in model 2; lifestyle characteristics (current smoking,alcohol intake, and SQUASH score) in model 3; transplantation-related data (transplant vintage andeGFR) in model 4; immunosuppressive therapy (prednisolone dose and use of calcineurin inhibitors)in model 5; and inflammation (high sensitivity C-reactive protein (hs-CRP)) in model 6. NODATand graft failure were censored at the date of last follow-up or death. Models were checked for thefulfillment of the assumptions of Cox regression analysis. The assumptions were met.

Furthermore, we performed prespecified analyses in which we tested for potentialeffect-modification by dietary intake of antioxidant fatty acids using multiplicative interaction termsover the fully adjusted model. In case of significant effect-modification, we proceeded with stratifiedprospective analyses for the concerned variable. Cut-off points of originally continuous variables usedin the stratified analyses were determined so they would allow for an as much as possible similarnumber of events in each subgroup, and thus allow for similar statistical power for the assessmentof the primary association under study (MDA concentration and NODAT) in each subgroup afterstratification of the overall population. Since the number of events was reduced in each subgroupthese analyses were adjusted analogous to model 3 of the overall prospective analyses to avoidoverfitting. Also, since the dietary intake of antioxidant fatty acids could also be a potential confounder,we investigated if adjusting for this variable changed the association between MDA and NODAT.

For all statistical analyses, a statistical significance level of p ≤ 0.05 (two-tailed) was used, exceptfor the effect-modification analyses where the significance level was p ≤ 0.1 (two-tailed) [31].

3. Results

3.1. Baseline Characteristics

In total 516 RTR (57% men) were included in the analyses with a mean ± SD age of 51 ± 13 years.Patients were included at a median of 5.2 (IQR 2.0–12.2) years after transplantation. The medianplasma MDA concentration was 2.55 (IQR 1.92–3.66) µmol/L. Baseline characteristics of the overallRTR population are shown in Table 1. In crude linear regression analyses, glucose concentration

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had a significant direct association with plasma MDA concentration (β = 0.10, p = 0.02), which wasnot modified after adjustment for age, sex, and eGFR. Other variables with significant associationswith plasma MDA concentration after adjustment were eGFR (β = 0.10, p = 0.03) and leucocytesconcentration (β = 0.10, p = 0.03). A final reduced model of baseline variables obtained throughbackwards linear regression analyses (α = 0.05) included glucose concentration (β = 0.11, p = 0.02),eGFR (β = 0.08, p = 0.09) leucocytes concentration (β = 0.10, p = 0.03), HDL concentration (β = 0.10,p = 0.04), and alcohol intake (β = −0.09, p = 0.07) (Table 1).

Table 1. Baseline characteristics of the study population and its association with circulatingmalondialdehyde (MDA) (n = 516).

Baseline Characteristics

Plasma MDA, Ln

Linear Regression ¥ Adjusted LinearRegression †

Backwards LinearRegression §

Std. β Std. β Std. β

Plasma MDA, µmol/L 2.55 (1.92–3.66) – – –Demographic and anthropometric

Age, years 52 ± 13 0.01 0.02Male sex, n (%) 292 (57) −0.06 * −0.07 * ~Weight, kg 79.0 ± 15.4 −0.04 −0.01Height, cm 174 ± 10 −0.04 0.02BMI, kg/m2 26.0 ± 4.4 −0.03 −0.02Waist, cm a 96.4 ± 13.7 −0.07 * −0.05

Glucose and lipids metabolismGlucose, mmol/L(mg/dL) b 5.16 (93) ± 0.64 (11) 0.10 ** 0.11 ** 0.12 **HbA1c, % c 5.67 ± 0.36 0.05 0.05Impaired fasting glucose, n (%) 122 (24) 0.06 * 0.07 * ~Total cholesterol, mmol/L 5.12 ± 1.11 0.05 0.05HDL cholesterol, mmol/L d 1.3 (1.1–1.7) 0.09 ** 0.06 * 0.09 **LDL cholesterol, mmol/L d 3.0 ± 0.9 −0.04 −0.04Triglycerides, mmol/L e 1.62 (1.21–2.16) 0.03 0.05

Transplantation-related dataTime after transplant, years 5.2 (2.0–12.2) 0.03 0.02Living donor, n (%) 187 (36) 0.07 * 0.07 * ~Pre-emptive, n (%) 92 (18) 0.03 0.02

Immunosuppressive therapyAcute rejection treatment, n (%) 124 (24) 0.06 * 0.08 * ~Use of calcineurin inhibitors

Tacrolimus, n (%) 89 (17) −0.01 0.02Cyclosporine, n (%) 194 (38) −0.02 −0.01

Use of proliferation inhibitorsAzathriopine, n (%) 95 (18) 0.01 0.01Mycophenolic acid, n (%) 340 (66) 0.03 0.03

Prednisolone cumulative dose, g 16.9 (5.8–36.3) 0.02 0.02Cardiovascular history

History of CV disease, n (%) f 204 (40) 0.01 0.01SBP, mmHg e 135 ± 17 −0.03 −0.01DBP, mmHg e 83 ± 11 0.05 0.08 * ~Use of antihypertensivemedication, n (%) 448 (87) −0.05 −0.02

Graft function and inflammationSerum creatinine, µmol/L d 123 (100–159) −0.07 * 0.12 * ~eGFR (CKD-EPI), mL/mind d 53 ± 20 0.10 ** 0.10 ** ~Protein excretion, g/day 0.18 (0.02–0.32) 0.01 0.04hs-CRP, mg/L g 1.4 (0.6–3.8) <0.01 <0.01Leucocytes, × 109/L e 7.8 (6.3–9.6) 0.10 ** 0.09 ** 0.12 **

NutritionPlasma albumin, g/L d 43.3 ± 3.0 0.002 −0.003Kcal intake, kcal/day h 2189 ± 617 −0.002 0.01Fatty acids intake h

n-6 LA, g/day ∧ 15 (13–19) 0.03 0.05n-6 AA, g/day ∧ 0.05 (0.04–0.06) 0.02 0.02n-3 ALA, g/day ∧ 1.25 (1.02–1.60) 0.01 0.03n-3 EPA, g/day ∧ 0.04 (0.01–0.09) 0.05 0.05n-3 DHA, g/day ∧ 0.06 (0.03–0.13) 0.06 0.06

LifestyleCurrent smokers, n (%) i 67 (13) −0.01 0.002Alcohol intake, g/day h 2.92 (0.04–11.52) −0.08 * −0.08 * ~SQUASH-score, intensity × hours 5555 (2640–8513) −0.02 <0.01

* p value < 0.20; ** p value < 0.05. ¥ Crude linear regression analysis. † Linear regression analysis adjusted for age,sex, and eGFR. § Stepwise backwards linear regression analysis; for inclusion and exclusion in this analysis, p Valueswere set at 0.2 and 0.05, respectively. ~ Excluded from the final model. Data available in: a 499, b 514, c 495, d 455, e

515, f 398, g 484, h 468, i 490 patients. MDA, malondialdehyde; Std. β, standarized B coefficient; eGFR, estimatedglomerular filtration rate; CV, cardiovascular; HbA1c, glycosylated hemoglobin; hs-CRP, high-sensitive C-reactiveprotein; kcal, kilocalories; LA, linoleic acid; AA, arachidonic acid; ALA, α-lipoic acid; EPA, eicosapentaenoic acid;DHA, docosahexaenoic acid. ∧ Adjusted for total caloric intake according to the residual method.

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3.2. Prospective Analyses on NODAT

During a median follow-up of 5.3 (IQR 4.6–6.0) years, NODAT developed in 56 (11%) RTR.Kaplan–Meier curves for NODAT development by tertiles of RTRs according to circulating MDA areshown in Figure 1. NODAT distribution was significantly different according to the log-rank test(p = 0.02). Cox regression analyses showed that plasma MDA concentration is inversely associated withthe risk of NODAT (HR, 0.61; 95% CI, 0.41–0.92 per 1-SD; p = 0.02). This association was independentof adjustment for demographic and anthropometric factors, metabolism-related variables, lifestylefactors, transplantation-related data, immunosuppressive medication, and inflammation (HR, 0.55;95% CI, 0.36–0.83 per 1-SD; p < 0.01) (Table 2).

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3.2. Prospective Analyses on NODAT

During a median follow-up of 5.3 (IQR 4.6–6.0) years, NODAT developed in 56 (11%) RTR. Kaplan–Meier curves for NODAT development by tertiles of RTRs according to circulating MDA are shown in Figure 1. NODAT distribution was significantly different according to the log-rank test (p = 0.02). Cox regression analyses showed that plasma MDA concentration is inversely associated with the risk of NODAT (HR, 0.61; 95% CI, 0.41–0.92 per 1-SD; p = 0.02). This association was independent of adjustment for demographic and anthropometric factors, metabolism-related variables, lifestyle factors, transplantation-related data, immunosuppressive medication, and inflammation (HR, 0.55; 95% CI, 0.36–0.83 per 1-SD; p < 0.01) (Table 2).

Figure 1. Kaplan–Meier curves for NODAT according to tertiles of plasma MDA concentration in RTR. Tertile 1: <2.15 µmol/L; Tertile 2: 2.15–3.09 µmol/L; Tertile 3: >3.09 µmol/L. p value was calculated by Log-rank (Mantel cox) test.

Table 2. Plasma MDA concentration and new-onset diabetes after transplantation (NODAT) in renal transplant recipients (RTR, n = 516).

NODAT HR (95% CI) Per 1-SD p Crude model 0.61 (0.41–0.92) 0.02

Model 1 0.63 (0.42–0.94) 0.02 Model 2 0.54 (0.36–0.83) <0.01 Model 3 0.54 (0.35–0.82) <0.01 Model 4 0.56 (0.37–0.85) <0.01 Model 5 0.55 (0.36–0.83) <0.01 Model 6 0.55 (0.36–0.83) <0.01

In total, 56 (11%) RTR developed NODAT. Model 1: crude model plus adjustment for demographic and anthropometric characteristics. Model 2: model 1 plus adjustment for metabolism-related variables. Model 3: model 2 plus adjustment for lifestyle characteristics. Model 4: model 3 plus adjustment for transplantation-related data. Model 5: model 4 plus adjustment for immunosuppressive therapy. Model 6: model 5 plus adjustment for inflammation.

3.3. Secondary Analysis on MDA and NODAT

In effect-modification analyses, we found that the association between MDA and the risk of NODAT was significantly modified by vitamin E, linoleic acid (LA), and α-lipoic acid (ALA) intake in regular diet (pinteraction = 0.06, 0.02, and 0.02; respectively). Thus, we performed stratified prospective analyses by subgroups of RTR according to vitamin E intake (≤ or >13.64 mg/day), LA intake (≤ or

Figure 1. Kaplan–Meier curves for NODAT according to tertiles of plasma MDA concentration in RTR.Tertile 1: <2.15 µmol/L; Tertile 2: 2.15–3.09 µmol/L; Tertile 3: >3.09 µmol/L. p value was calculated byLog-rank (Mantel cox) test.

Table 2. Plasma MDA concentration and new-onset diabetes after transplantation (NODAT) in renaltransplant recipients (RTR, n = 516).

NODAT HR (95% CI) Per 1-SD p

Crude model 0.61 (0.41–0.92) 0.02Model 1 0.63 (0.42–0.94) 0.02Model 2 0.54 (0.36–0.83) <0.01Model 3 0.54 (0.35–0.82) <0.01Model 4 0.56 (0.37–0.85) <0.01Model 5 0.55 (0.36–0.83) <0.01Model 6 0.55 (0.36–0.83) <0.01

In total, 56 (11%) RTR developed NODAT. Model 1: crude model plus adjustment for demographic andanthropometric characteristics. Model 2: model 1 plus adjustment for metabolism-related variables. Model3: model 2 plus adjustment for lifestyle characteristics. Model 4: model 3 plus adjustment for transplantation-relateddata. Model 5: model 4 plus adjustment for immunosuppressive therapy. Model 6: model 5 plus adjustmentfor inflammation.

3.3. Secondary Analysis on MDA and NODAT

In effect-modification analyses, we found that the association between MDA and the risk ofNODAT was significantly modified by vitamin E, linoleic acid (LA), and α-lipoic acid (ALA) intake inregular diet (pinteraction = 0.06, 0.02, and 0.02; respectively). Thus, we performed stratified prospectiveanalyses by subgroups of RTR according to vitamin E intake (≤ or >13.64 mg/day), LA intake(≤ or >14 g/day) and ALA intake (≤ or > or 1.24 g/day), in which cut-off points were determined

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so they would allow an as much as possible similar number of events in each subgroup. In eachsubgroup we assessed the association of MDA with development of NODAT and found that MDA wassignificantly inversely associated with the risk of NODAT in RTR with vitamin E intake >13.6 mg/day(HR, 0.52; 95% CI, 0.29–0.94 per 1-SD; p = 0.03), LA intake >14g/day (HR, 0.49; 95% CI 0.28–0.86 per1-SD; p = 0.01), or ALA intake >1.24g/day (HR 0.42, 95% CI, 0.23–0.76 per 1-SD; p < 0.01), but not inthe subgroups of relatively low intake (Figure 2).

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>14 g/day) and ALA intake (≤ or > or 1.24 g/day), in which cut-off points were determined so they would allow an as much as possible similar number of events in each subgroup. In each subgroup we assessed the association of MDA with development of NODAT and found that MDA was significantly inversely associated with the risk of NODAT in RTR with vitamin E intake >13.6 mg/day (HR, 0.52; 95% CI, 0.29–0.94 per 1-SD; p = 0.03), LA intake >14g/day (HR, 0.49; 95% CI 0.28–0.86 per 1-SD; p = 0.01), or ALA intake >1.24g/day (HR 0.42, 95% CI, 0.23–0.76 per 1-SD; p < 0.01), but not in the subgroups of relatively low intake (Figure 2).

Figure 2. Stratified analysis of the association of plasma MDA concentrations with NODAT. * For the association between MDA and NODAT. HR are reported per 1-SD increase in plasma MDA concentration. Nutrient intake was adjusted for total energy intake according to the residual method. HR adjusted for age, sex, BMI, plasma glucose, HbA1c, smoking status, alcohol intake, and SQUASH score are shown.

Further, we performed Cox regression analyses with adjustment for these variables to explore if they might also be potential confounders. The association between MDA and NODAT was not significantly modified by additional adjustment for vitamin E intake (HR, 0.52; 95% CI, 0.34–0.81 per 1-SD; p < 0.01), ALA intake (HR, 0.55; 95% CI, 0.36–0.83 per 1-SD; p < 0.01), or LA intake (HR, 0.56; 95% CI, 0.37–0.84 per 1-SD; p < 0.01).

3.4. Prospective Analysis on All-Cause Mortality, Cardiovascular Mortality, and Graft Failure

During the same median follow up of 5.3 (IQR 4.6–5.9) years, 86 (17%) RTRs died, 29 (6%) from cardiovascular cause and 57 (11%) developed graft failure. In crude Cox regression analysis, plasma MDA concentration was not significantly associated with the risk of all-cause mortality (HR, 0.96; 95% CI, 0.73–1.25 per 1-SD; p = 0.74), cardiovascular mortality (HR, 0.81; 95% CI, 0.58–1.13 per 1-SD; p = 0.21), nor death-censored graft failure (HR, 0.89; 95% CI, 0.65–1.23 per 1-SD; p = 0.49). Further adjustments did not materially change these findings (Tables S1, S2 and S3).

4. Discussion

In a large cohort of stable RTR, we showed first that plasma MDA is directly associated with plasma glucose concentration. Second, plasma MDA is inversely associated with long-term risk of NODAT. This association remained present independent of potential confounders, including BMI, baseline glucose concentration and immunosuppressive therapy. Daily dietary intake of antioxidant fatty acids, e.g., vitamin E and ALA was a significant effect-modifier of this association. No association was found whatsoever between MDA and mortality, cardiovascular mortality, or graft

Figure 2. Stratified analysis of the association of plasma MDA concentrations with NODAT. * Forthe association between MDA and NODAT. HR are reported per 1-SD increase in plasma MDAconcentration. Nutrient intake was adjusted for total energy intake according to the residual method.HR adjusted for age, sex, BMI, plasma glucose, HbA1c, smoking status, alcohol intake, and SQUASHscore are shown.

Further, we performed Cox regression analyses with adjustment for these variables to exploreif they might also be potential confounders. The association between MDA and NODAT was notsignificantly modified by additional adjustment for vitamin E intake (HR, 0.52; 95% CI, 0.34–0.81 per1-SD; p < 0.01), ALA intake (HR, 0.55; 95% CI, 0.36–0.83 per 1-SD; p < 0.01), or LA intake (HR, 0.56; 95%CI, 0.37–0.84 per 1-SD; p < 0.01).

3.4. Prospective Analysis on All-Cause Mortality, Cardiovascular Mortality, and Graft Failure

During the same median follow up of 5.3 (IQR 4.6–5.9) years, 86 (17%) RTRs died, 29 (6%) fromcardiovascular cause and 57 (11%) developed graft failure. In crude Cox regression analysis, plasmaMDA concentration was not significantly associated with the risk of all-cause mortality (HR, 0.96;95% CI, 0.73–1.25 per 1-SD; p = 0.74), cardiovascular mortality (HR, 0.81; 95% CI, 0.58–1.13 per 1-SD;p = 0.21), nor death-censored graft failure (HR, 0.89; 95% CI, 0.65–1.23 per 1-SD; p = 0.49). Furtheradjustments did not materially change these findings (Tables S1–S3).

4. Discussion

In a large cohort of stable RTR, we showed first that plasma MDA is directly associated withplasma glucose concentration. Second, plasma MDA is inversely associated with long-term riskof NODAT. This association remained present independent of potential confounders, includingBMI, baseline glucose concentration and immunosuppressive therapy. Daily dietary intake ofantioxidant fatty acids, e.g., vitamin E, LA and ALA were a significant effect-modifier of this association.No association was found whatsoever between MDA and all-cause mortality, cardiovascular mortality,or graft failure. These findings agree with developing evidence that proposes that oxidative statusplays an important role in glucose homeostasis [10–13].

Experimental work has shown that reactive oxygen species (ROS) are part of intracellular insulinsignal transmission [10,11]. ROS are upregulated in response to insulin and help to further up-regulate

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glucose-metabolism associated pathways related, e.g., with insulin-induced aerobic glycolysis [13].Furthermore, ROS seem to have an effect on enzymes essential for catalytic activity, increasing glucoseintake by skeletal muscle cells and glucose transport in adipocytes [11]. Also, human studies haveshown that: (i) patients with severe deficiency of plasmatic antioxidants maintain supranormal insulinsensitivity, compared to healthy subjects, even if they are obese [12] and (ii) antioxidant moleculessupplementation abrogates the usually generated increase in insulin sensitivity of patients on exerciseinterventions [32]. The current study, performed in a high-risk of new-onset diabetes population,provides for the first-time prospective evidence in line with aforementioned basic studies, and mayfurther support the postulate of James Watson, according to which, diabetes mellitus may be causedby an incapacity of the cell to produce an oxidative redox environment [14].

Controversy may arise from data that has shown higher plasma MDA concentration in patientswith diabetes mellitus than in healthy controls [8], and in patients who develop diabetes-relatedcomplications than in those without them [9]. However, it is known that ROS—as intracellularmessengers—can generate opposite cellular effects. ROS can activate specific pathways whose productsinterfere with insulin signaling, e.g., the activation of the redox-sensitive nuclear factor-kappa beta(NF-kB) leads to the expression of cytokines such as tumoral necrosis factor α (TNF-α), and interleukins(ILs) such as IL-1β and IL-6 and all these products have a quenching effect on insulin signaling [11].On the other hand, as mentioned before, ROS can activate signaling pathways important to fulfilinsulin functions. Also, they are known to be themselves and stimuli to increase cellular antioxidantcapacity [33] by the activation of specific response elements known as Nuclear factor-erythroidrelated factor 2- antioxidant response elements (Nrf2-ARE); this induction of endogenous antioxidantmechanisms by ROS has been specifically named mitochondrial hormesis and has gained interest in thelast years [34], as it is proposed that, contrary to traditional thinking, ROS are not merely deleteriousbut they are necessary to reach oxidative balance inside the cell. Intensity, location, duration, andconcentration of the oxidant stimulus seem to be crucial in defining whether ROS have a physiologicalor a pathological outcome. However, the specific thresholds that spawn the differential responses havenot been determined yet [10,11]. This also might be a potential explanation of why studies regardingantioxidant supplementation have not shown to be beneficial in RTR [35], and why we did not find anassociation between OS and mortality, cardiovascular mortality, or graft failure.

Our data also provided evidence that LA, ALA, and vitamin E intake modify the associationbetween MDA and NODAT. Conceivable interpretations of these findings are as follows: MDA isformed after the peroxidation of double bonds of unsaturated fatty acids such as LA [7].Food containing important amounts of unsaturated fatty acids usually also contain substantial amountsof vitamin E, which prevents them from rancidification [36]. It is possible that in this context, highMDA concentration is a marker of a diet rich in antioxidants and unsaturated fatty acids, whichhas been suggested to reduce diabetes incidence [16,37]. However, when we adjusted for intakeof these nutrients to evaluate them as potential confounders, the association between MDA andNODAT remained materially unaltered. An alternative explanation might be the aforementionedNrf2-ARE pathway. This pathway has been of particular interest in the study of antioxidant moleculesas therapeutic interventions, because previous authors have proposed that these interventions couldshow beneficial results if they were combined with unsaturated fatty acids as precursors of oxidativestress [38]. The rationale is that through Nrf2-ARE pathway activation, provision of pro-oxidant andantioxidants agents would trigger the antioxidant cellular defenses [33], thus yielding cell preconditionto new oxidative challenges [39], and ultimately allowing cells to reach hormesis. This fits with ourfindings that high levels of MDA, although significantly inversely associated with NODAT in all ourpopulation, showed a stronger association in the patients with relatively higher intake of antioxidant inregular diet according to our subgroup analyses. Our findings might also support previous suggestionsof potential protector effect of antioxidant-rich diets against NODAT [17].

The present study has several strengths. To the extent of our knowledge, it comprises thelargest cohort of patients at risk of new-onset diabetes after transplantation in which the relationship

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between oxidative stress and NODAT has been evaluated. Moreover, our extensively phenotypedcohort allowed us to control for several potential confounders, among which anthropometricmeasurements, smoking status, baseline glucose metabolism markers, and immunosuppressivetherapy were accounted for. Furthermore, NODAT cases were diagnosed according to InternationalExpert Panel recommendations that were based on American Diabetes Association criteria [28],which agrees with usual clinical practice in transplant centers. Another strength of the study isthat we included only stable RTRs who were 1-year post-transplantation, resulting in exclusion oftransient post-transplantation hyperglycemia in NODAT diagnosis. Hyperglycemia is extremelycommon in the early posttransplant period and can occur as a result of rejection therapy, infections,and other critical conditions. Therefore, the formal diagnosis of NODAT in RTRs should only be basedon likely maintenance of immunosuppression, stable kidney function, and absent acute infections [29].The present study also has several limitations. It was carried out in a center with over-representationof Caucasian population, which calls prudence to extrapolation of our results to populations ofother ethnicities. Another limitation of our study is that we only measured MDA concentrations inbaseline samples. Most epidemiological studies use a single baseline measurement to predict outcomes,which adversely affects predictive properties of variables associated with outcomes. If intraindividualvariability of predictive biomarkers is taken into account, this results in strengthening of predictiveproperties that, despite sometimes containing considerable intraindividual day-to-day variation,also existed for single measurements of these biomarkers [40,41]. The higher the intraindividualday-to-day variation is, the greater one would expect the benefit of repeated measurement forprediction of outcomes [40,41]. Next, although MDA has been the most commonly used OS biomarkerin studies regarding glucose metabolism [9,10], further studies may want to account for other OSbiomarkers to further validate our findings. Finally, the observational nature of this study makes itdifficult to discern whether high levels of MDA are protective against NODAT or merely a marker oflower risk for NODAT; and, as with any observational study, residual confounding may have existeddespite the substantial number of potentially confounding factors for which we adjusted, includingwell identified risk factors for NODAT.

In conclusion, plasma MDA concentration is inversely and independently associated withlong-term risk of NODAT in stable RTR. This study provided for the first time relevant prospective dataon the role of oxidative stress on glucose metabolism in a high-risk of diabetes population. This mayfurther support already published basic studies and further promote studies to widen our knowledgeon the role of oxidative stress in the pathophysiological mechanisms leading to diabetes and NODAT,which might be of relevant use in exploring novel therapeutic approaches to prevent and treat NODAT;also, it indicates that studies exploring antioxidant supplementation in RTR should explore and reportmetabolic outcomes in the long-term.

Supplementary Materials: The following are available online at http://www.mdpi.com/2077-0383/8/4/453/s1,Table S1: Plasma MDA concentration and all-cause mortality in RTR, Table S2: Plasma MDA concentration andcardiovascular mortality in RTR, Table S3: Plasma MDA concentration and dead-censored graft failure in RTR.

Author Contributions: Data curation, M.Y.-C., C.G.S., A.W.G.-N., and S.J.L.B.; Formal analysis, M.Y.-C., C.G.S.and A.W.G.-N.; Funding acquisition, M.Y.-C., C.G.S., and S.J.L.B.; Investigation, R.O.B.G., S.P.B., G.R., T.E., R.R.,J.M.G., G.J.N. and S.J.L.B.; Methodology, G.R., T.E., J.M.G. and G.J.N.; Project administration, R.O.B.G., S.P.B.,G.J.N. and S.J.L.B.; Resources, R.O.B.G. and S.P.B.; Supervision, R.R., G.J.N., and S.J.L.B.; Writing – original draft,M.Y.-C. and C.G.S.; Writing – review & editing, M.Y.-C., C.G.S., R.R. and S.J.L.B.

Funding: This study was based on the TransplantLines Food and Nutrition Biobank and Cohort Study (TxL-FN),which was funded by the Top Institute Food and Nutrition of the Netherlands (grant A-1003). The study isregistered at clinicaltrials.gov under number NCT02811835.

Acknowledgments: Plasma MDA concentration was measured by Faizan et al. at the institute of Human Nutritionand Food Science, Christian Albrechts University of Kiel, Germany.

Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of thestudy; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision topublish the results.

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